Abstract
Background: Aging has often been linked to age-related vascular disorders. The elucidation of the putative genes and pathways underlying vascular aging likely provides useful insights into vascular diseases at advanced ages. Transcriptional regulatory network analysis is the key to describing genetic interactions between molecular regulators and their target gene transcriptionally changed during vascular aging.Results: A total of 469 differentially expressed genes were parsed into 6 modules. Among the incorporated sample traits, the most significant module related to vascular aging was associated with triglyceride and enriched with biological terms like proteolysis, blood circulation, and circulatory system process. The module associated with triglyceride was preserved in an independent microarray dataset, indicating the robustness of the identified vascular aging-related subnetwork. Additionally, Enpp5, Fez1, Kif1a, F3, H2-Q7, and their interacting miRNAs mmu-miR-449a, mmu-miR-449c, mmu-miR-34c, mmu-miR-34b-5p, mmu-miR-15a, and mmu-let-7, exhibited the most connectivity with external lipid-related traits. Transcriptional alterations of the hub genes Enpp5, Fez1, Kif1a, and F3, and the interacting microRNAs mmu-miR-34c, mmu-miR-34b-5p, mmu-let-7, mmu-miR-449a, and mmu-miR-449c were confirmed.Conclusion: Our findings demonstrate that triglyceride and free fatty acid-related genes are key regulators of age-related vascular dysfunction in mice and show that the hub genes for Enpp5, Fez1, Kif1a, and F3 as well as their interacting miRNAs mmu-miR-34c, mmu-miR-34b-5p, mmu-let-7, mmu-miR-449a, and mmu-miR-449c, could serve as potential biomarkers in vascular aging.Methods: The microarray gene expression profiles of aorta samples from 6-month old mice (n=6) and 20-month old mice (n=6) were processed to identify nominal differentially expressed genes. These nominal differentially expressed genes were subjected to a weighted gene co-expression network analysis. A network-driven integrative analysis with microRNAs and transcription factors was performed to define significant modules and underlying regulatory pathways associated with vascular aging, and module preservation test was conducted to validate the age-related modules based on an independent microarray gene expression dataset in mice aorta samples including three 32-week old wild-type mice (around 6-month old) and three 78-week old wild-type mice (around 20-month old). Gene ontology and protein-protein interaction analyses were conducted to determine the hub genes as potential biomarkers in the progress of vascular aging. The hub genes were further validated with quantitative real-time polymerase chain reaction in aorta samples from 20 young (6-month old) mice and 20 old (20-month old) mice.
Highlights
Vascular aging is characterized by structural and functional alterations of the vascular wall, deteriorating vascular integrity and vessel homeostasis, including increased luminal diameter with wall remodeling and augmented intimal and medial thickening, reorganization of the extracellular matrix with altered collagen, and elastin content and calcifications [1]
A network-driven integrative analysis with microRNAs and transcription factors was performed to define significant modules and underlying regulatory pathways associated with vascular aging, and module preservation test was conducted to validate the age-related modules based on an independent microarray gene expression dataset in mice aorta samples including three 32-week old wild-type mice and three 78-week old wild-type mice
It is evident that processes involving immune responses and oxidative stress occur in vascular aging [11]
Summary
Vascular aging is characterized by structural and functional alterations of the vascular wall, deteriorating vascular integrity and vessel homeostasis, including increased luminal diameter with wall remodeling and augmented intimal and medial thickening, reorganization of the extracellular matrix with altered collagen, and elastin content and calcifications [1]. These changes may increase cardiovascular morbidity and mortality by leading unequivocally to a number of detrimental changes in the cardiovascular system that are discriminated with atherosclerotic pathology [2]. Transcriptional regulatory network analysis is the key to describing genetic interactions between molecular regulators and their target gene transcriptionally changed during vascular aging
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